The Digital Twin of the City of Zurich for Urban Planning

Speakers: Schrotter, G.; Hürzeler, C.
Published at 19/06/2023 Last update 19/06/2023
Application case

Population growth will confront the City of Zurich with a variety of challenges in the coming years, as the increase in the number of inhabitants and jobs will lead to densification and competing land uses. The tasks for the city administration have become more complex, whereas tools and methods are often based on traditional, static approaches while involving a limited number of citizens and stakeholders in relevant decisions. The digital transformation of more and more pieces of the planning and decision-making process will make both increasingly more illustrative, easier to understand and more comprehensible. An important data basis for these processes is the digital twin of the City of Zurich. 3D spatial data and their models transform themes of the city, such as buildings, bridges, vegetation, etc., to the digital world, are being updated when required, and create advantages in digital space. These benefits need to be highlighted and published. An important step in public awareness is the release of 3D spatial data under Open Government Data. This allows the development of applications, the promotion of understanding, and the simplification of the creation of different collaborative platforms. By visualization and analysis of digital prototypes and the demonstration of interactions with the built environment, scenarios can be digitally developed and discussed in decision-making bodies. Questions about the urban climate can be simulated with the help of the digital twin and results can be linked to the existing 3D spatial data. Thus, the 3D spatial data set, the models and their descriptions through metadata become the reference and must be updated according to the requirements. Depending on requirements and questions, further 3D spatial data must be added. The description of the 3D spatial data and their models or the lifecycle management of the digital twin must be carried out with great care. Only in this way, decision processes can be supported in a comprehensible way.